Anomalies are rare observations (eg, data records or events) that deviate significantly from
the others in the sample. Over the past few decades, research on anomaly mining has …

Anomaly detection has been used for decades to identify and extract anomalous
components from data. Many techniques have been used to detect anomalies. One of the …

Deep learning approaches to anomaly detection (AD) have recently improved the state of
the art in detection performance on complex data sets, such as large collections of images or …

Detecting outliers is a significant problem that has been studied in various research and
application areas. Researchers continue to design robust schemes to provide solutions to …

Over the past decade, we have witnessed an enormous amount of research effort dedicated
to the design of efficient outlier detection techniques while taking into consideration …

Abstract Information and Communication Technology (ICT) has a great impact on social
wellbeing, economic growth and national security in todays world. Generally, ICT includes …

The massive data generated by the Internet of Things (IoT) are considered of high business
value, and data mining algorithms can be applied to IoT to extract hidden information from …

Network anomaly detection is an important and dynamic research area. Many network
intrusion detection methods and systems (NIDS) have been proposed in the literature. In this …

With the continuous increase in cyberattacks over the past few decades, the quest to
develop a comprehensive, robust, and effective intrusion detection system (IDS) in the …

The COVID-19 pandemic has impelled the majority of schools and universities around the
world to switch to remote teaching. One of the greatest challenges in online education is …